9/1/2014: The NCBC Program has ended. Future initiatives will be announced through the NIH Big Data program.

NIH Roadmap National Centers for Biomedical Computing

The National Centers for Biomedical Computing (NCBC) are cooperative agreement awards that are funded under the NIH Common Fund. The Centers are intended to be the core of the networked national effort to build the computational infrastructure for biomedical computing in the nation, the National Program of Excellence in Biomedical Computing (NPEBC). There are seven funded Centers that cover systems biology, image processing, biophysical modeling, biomedical ontologies, information integration, and tools for gene-phenotype and disease analysis. The centers will create innovative software programs and other tools that enable the biomedical community to integrate, analyze, model, simulate, and share data on human health and disease. Each Center has Cores that are focused on (1) computational science, (2) biomedical computational science and (3) driving biological projects whose intent is to drive the interaction between computational and biomedical computational science. In addition to the Centers, the NIH has a number of active program announcements to develop collaborations with the biomedical research community—this includes announcements from the Biomedical Information Science and Technology Initiative (BISTI) and the Program for Collaborations with National Centers for Biomedical Computing. There are numerous efforts in education and training that emanate from the Centers and there is an annual all hands meeting.

Daniel Reed
Vice President for Research and Economic Development
Computational Science and Bioinformatics Chair
Professor of Computer Science, Electrical and Computer Engineering, and Medicine
University of Iowa, Iowa City, IA

Brian Shoichet
Professor, Dept. of Pharmaceutical Chemistry
University of California, San Francisco, CA

John Wooley
Assistant Vice Chancellor for Research
University of California, San Diego, La Jolla, CA

Keith Yamamoto
Vice Chancellor for Research
University of California, San Francisco, San Francisco, CA

i2b2 Summary:
The large and growing size of the healthcare system makes it imperative to understand what is happening to us, the recipients of healthcare, to be able to efficiently conduct research to improve healthcare delivery and to improve the state of biomedicine by advancing its science. i2b2, "Informatics for Integrating Biology and the Bedside" seeks to provide this instrumentation using the informational by products of healthcare and the biological materials accumulated through the delivery of healthcare. This complements existing efforts to create prospective cohort studies or trials outside the delivery of routine healthcare. In the first round of i2b2, we demonstrated that we could identify known adverse events and phenotypically select and then genotype patients for genetic association at approximately 1/10* of the price and less than l/10 of the time usually entailed to develop such populations for study.

The methodological challenge we have set ourselves for the next phase in i2b2 is the development of Virtual Cohort Studies (VCS) encompassing the population of a healthcare system as study subjects and asking questions of comparative effectiveness, unforeseen adverse events and identification of clinically relevant subpopulations including both clinical and genome-scale measures. We will be comparing the results of the VCS to those of carefully planned and executed cohort studies such as the Framingham Heart Study. VCS will require multiple methodological advances and tools development including in the disciplines of natural language processing, temporal reasoning, predictive modeling, biostatistics and machine learning.

VCS methods will be tested by two driving biology projects, the first studying a collection of autoimmune diseases and the second type 2 diabetes. In both projects, VCS methods will be applied to investigate the components of cardiovascular risk from the genetic to the epigenetic and including the full range of clinical history including medications exposure. A systems/integrative approach will be taken to identify commonalities in these risk profiles across these disparate disease domains. VCS methods will be shared with i2b2 user community under open source governance while i2b2 user community contributions are folded into the i2b2 toolkit.

The second challenge is to recognize and build on our success in creating a nationally and internationally adopted platform now active in over half of the newly awarded Centers for Translational Science, as well as other national and international academic health centers and businesses. By leveraging the creativity of the hundreds of members of our Academic Users' Group to take the additions that they have built or are about to build for added functionality for i2b2. By establishing shared open source governance mechanisms and the resources to incorporate these multiple highly useful and sought after modules, we plan to generate a stable and enduring i2b2 ecosystem.

NA-MIC Summary:
The National Alliance for Medical Imaging Computing (NA-MIC) is a multi-institutional, interdisciplinary team of computer scientists, software engineers, and medical investigators who develop computational tools for the analysis and visualization of medical image data. The purpose of the center is to provide the infrastructure and environment for the development of computational algorithms and open source technologies, and then oversee the training and dissemination of these tools to the medical research community. This world-class software and development environment serves as a foundation for accelerating the development and deployment of computational tools that are readily accessible to the medical research community. The team combines cutting-edge computer vision research (to create medical imaging analysis algorithms) with state of the art software engineering techniques (based on "extreme" programming techniques in a distributed, open-source environment) to enable computational examination of both basic neuroscience and neurological disorders. In developing this infrastructure resource, the team is significantly expanding upon proven open systems technology and platforms.

The driving biological projects initially come from the study of schizophrenia, but the methods are applicable to many other diseases. The computational tools and open systems technologies and platforms developed by NA-MIC is initially being used to study anatomical structures and connectivity patterns in the brain, derangements of which have long been thought to play a role in the etiology of schizophrenia. The overall analysis occurs at a range of scales, and across a range of modalities including diffusion MRI, quantitative EGG, and metabolic and receptor PET, and will potentially include microscopic, genomic, and other image data. It applies to image data from individual patients, and to studies executed across large populations. The data is taken from subjects across a wide range of time scales and will ultimately apply to a broad range of diseases in a broad range of organs.

Simbios also provides the biomedical community with simtk.org, a free, secure, archival, distributed software repository and development system, where researchers and computational scientists can gather to collectively pursue their interests in physics-based simulation of biological structures. Simtk.org presents individual projects that may include models, software, data, documentation, publications, and graphics. Simtk.org is also the home of the SimTK simulation toolkit, our open-source, professionally developed software that provides advanced capabilities for modeling geometry and dynamics and facilitates physics-based simulation of biological systems. The toolkit and associated training materials result from a close collaboration with biomedical scientists. Applications, such as OpenSim for neuromuscular dynamics simulations and OpenMM Zephyr for GPU-accelerated molecular dynamics, that are built using SimTK are also available on the site.

Simbios' broad dissemination efforts include (1) the Biomedical Computation Review, a magazine devoted to the science and tools in biocomputation, (2) Simbiome, a searchable inventory of high-quality commercial and academic bio-simulation tools, and (3) workshops and distance learning materials for biomedical scientists and students.

NCBO Summary:
The National Center for Biomedical Ontology (NCBO) is a consortium of leading biologists, clinicians, informaticians, and ontologists who develop innovative technology and methods that allow scientists to create, disseminate, and manage biomedical information and knowledge in machine-processable form. The vision for the NCBO is that all biomedical knowledge and data are disseminated on the Internet using principled ontologies, such that the knowledge and data are semantically interoperable and useful for furthering biomedical science and clinical care. The Center's resources include: the BioPortal, a web portal for accessing, visualizing, and biomedical ontologies; an integrated Open Biomedical Ontologies (OBO) library; and tools for accessing and using this biomedical information in research. The NCBO collaborates with Driving Biological Projects that involve the development and use of ontologies to annotate different types of biomedical information and to extract additional knowledge from this data. A key component of the NCBO is the dissemination plan to institute frequent, formal workshops to help investigators at the grass roots to design biomedical ontologies of more utility and of more lasting value. These workshops are part of a general endeavor to establish and test best practices in ontology-building and to disseminate these practices across an ever wider community in ways designed to assure comparability of data.

MAGNet Summary:
Cellular processes are determined by the concerted activity of thousands of genes, their products, and a variety of other molecules. This activity is coordinated by a complex network of biochemical interactions largely determined by molecular structures and physiochemical properties which control common intra and inter-cellular functions over a wide range of scales. At an increasing level of granularity, these may range from the formation/activation of transcriptional complexes, to the availability of a signaling pathway, all the way to complex, macroscopic cellular processes, such as cell adhesion. Understanding this organization is crucial for the elucidation of biological function and for framing associated health related applications in a quantitative, molecular context. Additionally, the emerging complexity of these molecular interactions in the cell calls for a new level of sophistication in the design of genome-wide computational approaches.

The National Center for the Multiscale Analysis of Genomic and Cellular Networks (MAGNet) addresses this challenge through the application of both knowledge-based and physics-based methods. The Center provides an integrative computational framework to organize molecular interactions in the cell into manageable context dependent components. Furthermore, it is developing a variety of interoperable computational models and tools that can leverage such a map of cellular interactions to elucidate important biological processes and to address a variety of biomedical applications.

iDASH Summary:
The National Center for integrating Data for analysis, Anonymization, and Sharing (iDASH) is comprised of a team of leading informaticians, clinicians, and computer scientists devoted to advancing scientific progress among biomedical researchers. It develops new algorithms, open-source tools, computational infrastructure, and services to increase the sharing and analyzing of data in prospective and retrospective studies in a secure, privacy-preserving environment. This development is motivated by our three Driving Biological Projects: Molecular Phenotyping of Kawasaki Disease, Post-Marketing Surveillance of Hematologic Medications, and Individualized Intervention to Enhance Physical Activity. iDASH will disseminate tools through annual workshops, presentations at major conferences, and scientific publications. A comprehensive web portal will be provided where users may download tools, upload data, and obtain documentation and training materials.

CCB Summary:
The Center for Computational Biology (CCB) studies the dynamic properties of biological shape, form and size using novel mathematical algorithms and advanced computational techniques based on statistical learning, spectral analysis and differential equations. CCB develops, validates and disseminates data and software tools for modeling, analysis and visualization of shape across the spectrum of space-and-time scales. These new methods are applied for longitudinal studies of brain development, HIV/AIDS induced dementia, schizophrenia, multiple sclerosis and animal brain models for health.

NCIBI Summary:
The Mission of the National Center for Integrative Biomedical Informatics (NCIBI) is to create targeted knowledge environments for molecular biomedical research that help guide experiments and enable new insights from the analysis of complex diseases. NCIBI develops efficient software tools, data integration methods, and systems modeling environments. The resulting NICIBI “suite of tools and data” facilitates rapid construction of context-appropriate molecular biology information schemas from experimental data, biomedical databases, and the published literature. These tools, together with laboratory and community data resources, have accelerated our assembly of relevant information for research on our three Driving Biological Projects (DBPs): Gene Fusion in Cancers, Major Organ-Specific Complications of Diabetes, and Co-Morbid Disease Associations of Bipolar Disorder. NCIBI is disseminating these tools, data, and their integration capabilities for applications through portal-enhanced outreach and innovative web-based interactive training and educational programs for our partners around the country and for the broader NIH community and potential new collaborators.